The present invention relates to a device for identifying and/or classifying movement patterns in an image sequence of a surveillance scene, the device including an interface for recording the image sequence, and a calculation module for determining an optical flow field in the surveillance scene by evaluating the image sequence. The present invention also relates to a related method and a computer program.
Video surveillance systems are used, for example, to monitor public places, train stations, streets, industrial complex, buildings, or the like. Video surveillance systems usually include one or more surveillance cameras that are directed toward surveillance scenes and transfer image data streams in the form of image sequences to an evaluation center. Although it used to be common for the image sequences to be evaluated by trained surveillance personnel, it has since become increasingly common for evaluations to be performed automatically using digital image processing. The main advantages of automated evaluations of this type are that personnel costs are markedly reduced, and that the surveillance quality remains consistent.
Movement patterns in surveillance scenes are often identified and/or classified by separating moving objects from the (substantially stationary) background in the scene, to track them over time, and to trigger an alarm if relevant movements are identified. In a first step of “object segmentation”, the method used typically evaluates the differences between the current camera image and a “scene reference image” that models the static scene background, in order to identify moving objects.
In a different approach, the optical flow in the surveillance scene is monitored by evaluating the image sequence. In the calculation of the optical flow, the translatory motions of pixels or image regions from one image to a subsequent image in the image sequence are evaluated and, based on these translatory motions, a vector field is created that depicts a direction and speed of translation for every pixel or region being investigated. In this approach, object segmentation is carried out by classifying objects that agree in terms of polar vectors, that is, in terms of optical flow, as belonging to one common object.